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SG Shinichi Goto
MK Mai Kimura
YK Yoshinori Katsumata
SG Shinya Goto
TK Takashi Kamatani
GI Genki Ichihara
SK Seien Ko
JS Junichi Sasaki
KF Keiichi Fukuda
MS Motoaki Sano
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The neural network was constructed and trained using the Keras framework [7] using TensorFlow [8] as backend. The neural network was trained using the back-propagation supervised training algorithm. The loss function of binary cross entropy was minimized using the RMSprop optimizer.

The c-statistics, best accuracy, threshold, sensitivity and specificity of the model and its 95% confidence interval (CI) were calculated using the bootstrap procedure with 2000 bootstrap rounds using the pROC package of R[9].

The statistical analysis of probability of urgent revascularization with each quartile of model output was done using R version 3.5.1. Fisher’s exact test was used to calculate the p value. P value <0.05 were considered as statistically significant.

Copyright and License information:  ©2019 Goto et al
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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